Introduction

My name is Gilbert Permalloo. I am a Research Project Officer and I am presently working on roots architecture and rhizosphere of wheat. I worked in sugarcane agronomy for about 24 years and I was doing a little bit of basic programming in Fortran 77 and GWBasic about 30 years ago. Most of my data manipulation and visualisation are done in Excel. I could not write any code in R before I joined Data School and I was spending lots of time working with data in spreadsheets. On the otherhand, I am amazed to witness every day the marvel that R can do with data manipulation and visualisation.

My Project

The aim of this project is to investigate the use of portable X-Ray fluorescense spectrocopy (pXRF) as a rapid method to quantify the amount of phosphorus accumulated in straw and grains. About 200 grab samples were taken from one of three trials for this study. Two large datasets are generated by the pXRF; the chemistry, which is composed of a wide range of chemical elemental composition quantified in ppm, whereas the beamspectra, are spectral values from the X-ray beams. R has been used to clean, tidy and re-organised the data, as well as for graphical display of data. Data for phosphorus have been extracted from the large pXRF generated-dataset and merged with a dataframe that contains unique identification numbers (SampleID) that links the data to the sample source and other tables that contain agronomical data for each sample.

Preliminary results

Some data have been displayed graphically to show any trends

This section will demonstrate the different visuals you might want use to show off your project. Don’t feel the need to go overboard, this is supposed to give a taste of the work you are doing rather than being a publication ready document.

To get tables formatting correctly, use knitr::kable to convert the table to html format. If you also want to have alternate row highlighting, pass the result to kable_styling('striped') from the kableExtra package.

Tables

Table 1: A table of data

country	continent	year	lifeExp	pop	gdpPercap
Afghanistan	Asia	1952	28.801	8425333	779.4453
Afghanistan	Asia	1957	30.332	9240934	820.8530
Afghanistan	Asia	1962	31.997	10267083	853.1007
Afghanistan	Asia	1967	34.020	11537966	836.1971
Afghanistan	Asia	1972	36.088	13079460	739.9811

Fig.1: pXRF instrument used to quantify amount of phosphorus in straw and grains

Plots from R

Figure 1: Amount of phosphorus (ppm) in straw vs in grains

Figure 2: Amount of phosphorus in straw and grains vs grain yield

Your figure and table captions are automatically numbered and can be referenced in the text if needed: see eg. Table 1 and Figure ??

My Digital Toolbox

What digital tools have you been using in your project? Which ones have you learned since starting Data School?

You can use all the usual R markdown features in writing a project summary, including lists:

• R - dplyr, ggplot, …
• Python
• SQL

My time went …

What parts of the project took the most time and effort? Were there any surprising challenges you encountered, and how did you solve them?

Next steps

What further steps do you wish your project could take? Or are there any new digital skills that you are keen to develop as a result of your involvement in the Data School?

My Data School Experience

This poster is mostly about your synthesis project. However we would also like to hear about other parts of your Data School experience. What aspects of the program did you really enjoy? How have you been applying the skills you have learned in your daily work? Have you been able to transfer this knowledge to your team members? Concrete examples demonstrating this would be useful here (meetings/talks/collaborations/new roles). Any descriptions of the personal impact the program has had are welcome here as well!